However, the lack of centralized coordination in decentralized stochastic optimization also raises concerns on robustness. Some of the agents might be malfunctioning or even malicious. Due to data corruptions, equipment failures or cyber-attacks, they can send faulty values to their neighbors and bias the optimization process. We consider a general Byzantine attack model [1]}, in which the Byzantine agents are omniscient and can arbitrarily modify the values sent to other agents. Such an attack model imposes no restrictions on the adversaries and is worst-case. The purpose of this paper is to develop a Byzantine-robust decentralized stochastic optimization method.
